Genetic-genomic replication to identify candidate mouse atherosclerosis modifier genes

Abstract

Objective: Genetics plays a large role in atherosclerosis susceptibility in humans and mice. We attempted to confirm previously determined mouse atherosclerosis-associated loci and use bioinformatics and transcriptomics to create a catalog of candidate atherosclerosis modifier genes at these loci.

Methods and results: A strain intercross was performed between AKR and DBA/2 mice on the apoE(-/-) background generating 166 F2 progeny. Using the phenotype log10 of the aortic root lesion area, we identified 3 suggestive atherosclerosis quantitative trait loci (Ath QTLs). When combined with our prior strain intercross, we confirmed 3 significant Ath QTLs on chromosomes 2, 15, and 17, with combined logarithm of odds scores of 5.9, 5.3, and 5.6, respectively, which each met the genome-wide 5% false discovery rate threshold. We identified all of the protein coding differences between these 2 mouse strains within the Ath QTL intervals. Microarray gene expression profiling was performed on macrophages and endothelial cells from this intercross to identify expression QTLs (eQTLs), the loci that are associated with variation in the expression levels of specific transcripts. Cross tissue eQTLs and macrophage eQTLs that replicated from a prior strain intercross were identified. These bioinformatic and eQTL analyses produced a comprehensive list of candidate genes that may be responsible for the Ath QTLs.

Conclusions: Replication studies for clinical traits as well as gene expression traits are worthwhile in identifying true versus false genetic associations. We have replicated 3 loci on mouse chromosomes 2, 15, and 17 that are associated with atherosclerosis. We have also identified protein coding differences and multiple replicated eQTLs, which may be useful in the identification of atherosclerosis modifier genes.

Figure 1.

Log10 aortic root lesion atherosclerosis (Ath) quantitative trait locus (QTL) plots. The pink and blue lines show the logarithm of odds (LOD) plots for the prior and new crosses of AKR apoE^−/− and DBA/2 apoE^−/− mice, respectively. The black line shows the LOD plot for the combined analysis using cross as an additive covariate. In all analyses, sex was used as an interactive covariate.

Figure 2.

Example of a replicated cis‐eQTL between tissues (A and C) and between studies (A and B) of Sys1, an integral Golgi‐associated membrane protein. Means±SEM are shown adjacent to the individual values. P and R² values were obtained by linear regression with sex as an additive covariate. eQTL indicates expression quantitative trait loci; BMM, bone marrow macrophage; EC, endothelial cell.

Figure 3.

Venn diagram of the overlap between the cis‐eQTL in the new cross and the old cross. Transcripts were limited to only the transcripts that were called present in both and had corresponding probe between the platforms. eQTL indicates expression quantitative trait loci.

Figure 4.

An example of a replicating trans‐eQTL on chromosome 4 for the Lamb2 gene residing on chromosome 9. eQTL indicates expression quantitative trait loci; LOD, logarithm of odds.